Milk Composition of Asian Elephants (Elephas maximus) in a Natural Environment in Myanmar during Late Lactation

The nutritional content of milk from free-living Asian elephants has not previously been reported, despite being vital for better management of captive populations. This study analyzed both milk composition and consumed plant species of Asian elephants managed in their natural environment in Myanmar. Longitudinal samples (n = 36) were obtained during both the wet and the dry season from six mature females in mid to late lactation in 2016 and 2017. Milk composition averaged 82.44% water, with 17.56% total solids containing 5.23% protein, 15.10% fat, 0.87% ash, and 0.18 µg/mL vitamin E. Solids and protein increased with lactation month. Total protein in milk was higher during the wet vs. the dry season. Observed factors linked with maternal (age, parity, size and origin) and calf traits (sex) had significant associations with milk nutrient levels. Primary forages consumed contained moderate protein and fiber. Higher dietary protein during the wet season (11–25%) compared to the dry season (6–19%) may be linked with increased milk protein observed. Our results call for further field studies of milk and diet composition, over entire seasons/lactation periods, and across maternal and calf traits, to improve feeding management, with an overall goal of maximized health and survival

Children, parents, and pets exercising together (CPET) randomised controlled trial: study rationale, design, and methods

Objectively measured physical activity is low in British children, and declines as childhood progresses. Observational studies suggest that dog-walking might be a useful approach to physical activity promotion in children and adults, but there are no published public health interventions based on dog-walking with children. The Children, Parents, and Pets Exercising Together Study aims to develop and evaluate a theory driven, generalisable, family-based, dog walking intervention for 9-11 year olds

Reconstruction of cellular variability from spatiotemporal patterns of Dictyostelium discoideum

Variability in cell properties can be an important driving mechanism behind spatiotemporal patterns in biological systems, as the degree of cell-to-cell differences determines the capacity of cells to locally synchronize and, consequently, form patterns on a larger spatial scale. In principle, certain features of spatial patterns emerging with time may be regulated by variability or, more specifically, by certain constellations of cell-to-cell differences. Similarly, measuring variability in a system (i.e. the spatial distribution of cell-cell differences) may help predict properties of later-stage patterns

Acceptance and Perception of Artificial Intelligence Usability in Eye Care (APPRAISE) for Ophthalmologists: A Multinational Perspective

Background: Many artificial intelligence (AI) studies have focused on development of AI models, novel techniques, and reporting guidelines. However, little is understood about clinicians' perspectives of AI applications in medical fields including ophthalmology, particularly in light of recent regulatory guidelines. The aim for this study was to evaluate the perspectives of ophthalmologists regarding AI in 4 major eye conditions: diabetic retinopathy (DR), glaucoma, age-related macular degeneration (AMD) and cataract. Methods: This was a multi-national survey of ophthalmologists between March 1st, 2020 to February 29th, 2021 disseminated via the major global ophthalmology societies. The survey was designed based on microsystem, mesosystem and macrosystem questions, and the software as a medical device (SaMD) regulatory framework chaired by the Food and Drug Administration (FDA). Factors associated with AI adoption for ophthalmology analyzed with multivariable logistic regression random forest machine learning. Results: One thousand one hundred seventy-six ophthalmologists from 70 countries participated with a response rate ranging from 78.8 to 85.8% per question. Ophthalmologists were more willing to use AI as clinical assistive tools (88.1%, n = 890/1,010) especially those with over 20 years' experience (OR 3.70, 95% CI: 1.10–12.5, p = 0.035), as compared to clinical decision support tools (78.8%, n = 796/1,010) or diagnostic tools (64.5%, n = 651). A majority of Ophthalmologists felt that AI is most relevant to DR (78.2%), followed by glaucoma (70.7%), AMD (66.8%), and cataract (51.4%) detection. Many participants were confident their roles will not be replaced (68.2%, n = 632/927), and felt COVID-19 catalyzed willingness to adopt AI (80.9%, n = 750/927). Common barriers to implementation include medical liability from errors (72.5%, n = 672/927) whereas enablers include improving access (94.5%, n = 876/927). Machine learning modeling predicted acceptance from participant demographics with moderate to high accuracy, and area under the receiver operating curves of 0.63–0.83. Conclusion: Ophthalmologists are receptive to adopting AI as assistive tools for DR, glaucoma, and AMD. Furthermore, ML is a useful method that can be applied to evaluate predictive factors on clinical qualitative questionnaires. This study outlines actionable insights for future research and facilitation interventions to drive adoption and operationalization of AI tools for Ophthalmology

Protein quality control: the who’s who, the where’s and therapeutic escapes

In cells the quality of newly synthesized proteins is monitored in regard to proper folding and correct assembly in the early secretory pathway, the cytosol and the nucleoplasm. Proteins recognized as non-native in the ER will be removed and degraded by a process termed ERAD. ERAD of aberrant proteins is accompanied by various changes of cellular organelles and results in protein folding diseases. This review focuses on how the immunocytochemical labeling and electron microscopic analyses have helped to disclose the in situ subcellular distribution pattern of some of the key machinery proteins of the cellular protein quality control, the organelle changes due to the presence of misfolded proteins, and the efficiency of synthetic chaperones to rescue disease-causing trafficking defects of aberrant proteins

Knocking-Down Cyclin A2 by siRNA Suppresses Apoptosis and Switches Differentiation Pathways in K562 Cells upon Administration with Doxorubicin

Cyclin A2 is critical for the initiation of DNA replication, transcription and cell cycle regulation. Cumulative evidences indicate that the deregulation of cyclin A2 is tightly linked to the chromosomal instability, neoplastic transformation and tumor proliferation. Here we report that treatment of chronic myelogenous leukaemia K562 cells with doxorubicin results in an accumulation of cyclin A2 and follows by induction of apoptotic cell death. To investigate the potential preclinical relevance, K562 cells were transiently transfected with the siRNA targeting cyclin A2 by functionalized single wall carbon nanotubes. Knocking down the expression of cyclin A2 in K562 cells suppressed doxorubicin-induced growth arrest and cell apoptosis. Upon administration with doxorubicin, K562 cells with reduced cyclin A2 showed a significant decrease in erythroid differentiation, and a small fraction of cells were differentiated along megakaryocytic and monocyte-macrophage pathways. The results demonstrate the pro-apoptotic role of cyclin A2 and suggest that cyclin A2 is a key regulator of cell differentiation. To the best of our knowledge, this is the first report that knocking down expression of one gene switches differentiation pathways of human myeloid leukemia K562 cells

Studies of a Ring-Cleaving Dioxygenase Illuminate the Role of Cholesterol Metabolism in the Pathogenesis of Mycobacterium tuberculosis

Mycobacterium tuberculosis, the etiological agent of TB, possesses a cholesterol catabolic pathway implicated in pathogenesis. This pathway includes an iron-dependent extradiol dioxygenase, HsaC, that cleaves catechols. Immuno-compromised mice infected with a ΔhsaC mutant of M. tuberculosis H37Rv survived 50% longer than mice infected with the wild-type strain. In guinea pigs, the mutant disseminated more slowly to the spleen, persisted less successfully in the lung, and caused little pathology. These data establish that, while cholesterol metabolism by M. tuberculosis appears to be most important during the chronic stage of infection, it begins much earlier and may contribute to the pathogen's dissemination within the host. Purified HsaC efficiently cleaved the catecholic cholesterol metabolite, DHSA (3,4-dihydroxy-9,10-seconandrost-1,3,5(10)-triene-9,17-dione; kcat/Km = 14.4±0.5 µM−1 s−1), and was inactivated by a halogenated substrate analogue (partition coefficient<50). Remarkably, cholesterol caused loss of viability in the ΔhsaC mutant, consistent with catechol toxicity. Structures of HsaC:DHSA binary complexes at 2.1 Å revealed two catechol-binding modes: bidentate binding to the active site iron, as has been reported in similar enzymes, and, unexpectedly, monodentate binding. The position of the bicyclo-alkanone moiety of DHSA was very similar in the two binding modes, suggesting that this interaction is a determinant in the initial substrate-binding event. These data provide insights into the binding of catechols by extradiol dioxygenases and facilitate inhibitor design

Exploring Statistical and Population Aspects of Network Complexity

The characterization and the definition of the complexity of objects is an important but very difficult problem that attracted much interest in many different fields. In this paper we introduce a new measure, called network diversity score (NDS), which allows us to quantify structural properties of networks. We demonstrate numerically that our diversity score is capable of distinguishing ordered, random and complex networks from each other and, hence, allowing us to categorize networks with respect to their structural complexity. We study 16 additional network complexity measures and find that none of these measures has similar good categorization capabilities. In contrast to many other measures suggested so far aiming for a characterization of the structural complexity of networks, our score is different for a variety of reasons. First, our score is multiplicatively composed of four individual scores, each assessing different structural properties of a network. That means our composite score reflects the structural diversity of a network. Second, our score is defined for a population of networks instead of individual networks. We will show that this removes an unwanted ambiguity, inherently present in measures that are based on single networks. In order to apply our measure practically, we provide a statistical estimator for the diversity score, which is based on a finite number of samples

14-3-3ζ Interacts with Stat3 and Regulates Its Constitutive Activation in Multiple Myeloma Cells

The 14-3-3 proteins are a family of regulatory signaling molecules that interact with other proteins in a phosphorylation-dependent manner and function as adapter or scaffold proteins in signal transduction pathways. One family member, 14-3-3ζ, is believed to function in cell signaling, cycle control, and apoptotic death. A systematic proteomic analysis done in our laboratory has identified signal transducers and activators of transcription 3 (Stat3) as a novel 14-3-3ζ interacting protein. Following our initial finding, in this study, we provide evidence that 14-3-3ζ interacts physically with Stat3. We further demonstrate that phosphorylation of Stat3 at Ser727 is vital for 14-3-3ζ interaction and mutation of Ser727 to Alanine abolished 14-3-3ζ/Stat3 association. Inhibition of 14-3-3ζ protein expression in U266 cells inhibited Stat3 Ser727 phosphorylation and nuclear translocation, and decreased both Stat3 DNA binding and transcriptional activity. Moreover, 14-3-3ζ is involved in the regulation of protein kinase C (PKC) activity and 14-3-3ζ binding to Stat3 protects Ser727 dephosphorylation from protein phosphatase 2A (PP2A). Taken together, our findings support the model that multiple signaling events impinge on Stat3 and that 14-3-3ζ serves as an essential coordinator for different pathways to regulate Stat3 activation and function in MM cells

Molecular marks for epigenetic identification of developmental and cancer stem cells

Epigenetic regulations of genes by reversible methylation of DNA (at the carbon-5 of cytosine) and numerous reversible modifications of histones play important roles in normal physiology and development, and epigenetic deregulations are associated with developmental disorders and various disease states, including cancer. Stem cells have the capacity to self-renew indefinitely. Similar to stem cells, some malignant cells have the capacity to divide indefinitely and are referred to as cancer stem cells. In recent times, direct correlation between epigenetic modifications and reprogramming of stem cell and cancer stem cell is emerging. Major discoveries were made with investigations on reprogramming gene products, also known as master regulators of totipotency and inducer of pluoripotency, namely, OCT4, NANOG, cMYC, SOX2, Klf4, and LIN28. The challenge to induce pluripotency is the insertion of four reprogramming genes (Oct4, Sox2, Klf4, and c-Myc) into the genome. There are always risks of silencing of these genes by epigenetic modifications in the host cells, particularly, when introduced through retroviral techniques. In this contribution, we will discuss some of the major discoveries on epigenetic modifications within the chromatin of various genes associated with cancer progression and cancer stem cells in comparison to normal development of stem cell. These modifications may be considered as molecular signatures for predicting disorders of development and for identifying disease states